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    Analysis of contractions in system graphs: Application to state estimation

    , Article 2021 IEEE International Conference on Autonomous Systems, ICAS 2021, 11 August 2021 through 13 August 2021 ; 2021 ; 9781728172897 (ISBN) Doostmohammadian, M ; Charalambous, T ; Shafie Khah, M ; Rabiee, H. R ; Khan, U. A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2021
    Abstract
    Observability and estimation are closely tied to the system structure, which can be visualized as a system graph-a graph that captures the inter-dependencies within the state variables. For example, in social system graphs such inter-dependencies represent the social interactions of different individuals. It was recently shown that contractions, a key concept from graph theory, in the system graph are critical to system observability, as (at least) one state measurement in every contraction is necessary for observability. Thus, the size and number of contractions are critical in recovering for loss of observability. In this paper, the correlation between the average-size/number of... 

    Network reconstruction under compressive sensing

    , Article Proceedings of the 2012 ASE International Conference on Social Informatics, SocialInformatics ; 2013 , Pages 19-25 ; 9780769550152 (ISBN) Siyari, P ; Rabiee, H. R ; Salehi, M ; Mehdiabadi, M. E ; Academy of Science and Engineering (ASE) ; Sharif University of Technology
    2013
    Abstract
    Many real-world systems and applications such as World Wide Web, and social interactions can be modeled as networks of interacting nodes. However, in many cases, one encounters the situation where the pattern of the node-to-node interactions (i.e., edges) or the structure of a network is unknown. We address this issue by studying the Network Reconstruction Problem: Given a network with missing edges, how is it possible to uncover the network structure based on certain observable quantities extracted from partial measurements? We propose a novel framework called CS-NetRec based on a newly emerged paradigm in sparse signal recovery called Compressive Sensing (CS). The results demonstrate that... 

    Significant pathological voice discrimination by computing posterior distribution of balanced accuracy

    , Article Biomedical Signal Processing and Control ; Volume 73 , 2022 ; 17468094 (ISSN) Pakravan, M ; Jahed, M ; Sharif University of Technology
    Elsevier Ltd  2022
    Abstract
    The ability to speak lucidly plays a key role in social relations. Consequently, the role of the larynx is quite important, and timely diagnosis of laryngeal diseases has proved to be crucial. In this study, a simple computational model for inverse of speech production model is employed to extract the glottal waveform using speech signal. This waveform has useful information about vocal folds performance in terms of providing evidence for distinguishing pathological disorders. Furthermore, obtaining the significance of classification results is important, because it leads to reliable inferences. This study utilizes the sustained vowel sound /a/ and a well-referenced database, namely MEEI. In...